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Based on the panel data of 20 countries in EU during the period of 2007–2019, this paper study the effect of energy market integration (EMI) on renewable energy development (RED). We develop a general equilibrium model to explain how EMI affect the RED and the role of different mechanisms. The empirical results reports that the European EMI increased both the consumption and power generation of renewable energy, which proves a significant positive effect of EMI on the RED. In line with our expectations of theoretical model, our estimates show that the increase of renewable energy consumption is mainly due to the fossil energy cost increased, technology advancement and regional environmental regulation strengthening. And the fossil energy cost is the main driven force which plays a completely mediating role between EMI and RED. Furthermore, we also observe a negative effect of FDI and industry structure on RED. • We establish a general equilibrium model to explain how EMI affect the RED and the role of different mechanisms. • The European EMI increased both the consumption and power generation of renewable energy. • The increase of renewable energy consumption is mainly due to the fossil energy price increased and technology advancement. • A negative effect of FDI and industry structure on RED is observed. [ABSTRACT FROM AUTHOR]

This paper examines the effect of per capita income, trade openness, energy consumption, and financial development on the ASEAN region's environmental degradation. We obtained data from the World Development Indicators (WDI) during the years 2001–2020 to test our research model. For analysis, we applied panel data techniques such as pooled least squares, fixed effects, generalized least squares (GLS), and two stages least squares (2SLS). We also conducted the causality analysis to determine the direction of the relationship among the models' variables. Our models' results show the validity of the environmental Kuznets curve (EKC) hypothesis in the ASEAN region as per capita income and its square term possess positive and negative coefficients. The results also show the presence of an N-shaped EKC in ASEAN region a deviation from the conventional literature. Moreover, the results illustrate that increasing energy consumption, trade openness, and financial development positively contribute to environmental degradation in ASEAN economies. The causality analysis shows a two-way causality between trade openness and financial development, and environmental degradation and trade openness. We observed oneway causality, running a) from energy consumption and per capita income towards financial development, b) from per capita income towards trade openness, and c) from financial development towards environmental degradation. The study's results contribute to the environmental degradation literature and provide a better understanding of environmental degradation for policymakers in ASEAN economies. • Energy consumption and financial development are the main driving forces behind environmental degradation in ASEAN Region. • Trade openness has improved the environmental quality in ASEAN Region. • The EKC hypothesis is valid in ASEAN Region. • The shape of the EKC hypothesis is N-Shaped in ASEAN Region. [ABSTRACT FROM AUTHOR]

The mechanism between financial agglomeration and environmental pollution is an important concern for both academia and policymaking. The main objective of this paper is to study the nonlinear impacts of financial agglomeration on environmental pollution. A theoretical framework was first constructed based on the scale effect, structure effect, and technology innovation effect of financial agglomeration and a Copeland-Taylor endogenous growth model. Using the panel data of 281 Chinese prefectural-level cities from 2003 to 2019, a panel threshold regression model was introduced to estimate the nonlinear association between financial agglomeration and environmental pollution. Industrial smoke (dust) emissions and industrial wastewater discharge were adopted to quantify current environmental pollution in China. The results show that financial agglomeration had a significant effect on improving the environment characterized by gradient thresholds; also notable is that 68.64% of the cities crossed the threshold value, entering the decelerating phase of financial agglomeration inhibiting environmental pollution. Both upgrading industrial structure and enhancing marketization could reduce environmental pollution, whereas increasing human capital, environmental regulation, and energy consumption had a deteriorating effect. The three channels for financial agglomeration to reduce environmental pollution were revealed to be financial scale, financial structure, and financial technology innovation. Our findings provide strong evidence for policymaking in sustainable development. [Display omitted] • Financial agglomeration (FA) is a crucial way to improve environment pollution (EP). • We built the theoretical framework of FA and EP based on the Copeland-Taylor model. • We tested the nonlinear impacts of FA on EP using the panel threshold model. • We revealed the transmission mechanism between FA and EP. [ABSTRACT FROM AUTHOR]

Considering the enlarging inter-provincial disparities in China as regards carbon emissions and carbon intensity (carbon emissions per unit gross domestic product), this paper is the first study to investigate the inter-provincial carbon imbalance by constructing and employing the Kaya-Zenga index. We use China's panel data of provincial-level carbon emissions over 1995–2016 to quantitatively measure the levels of inter-provincial imbalance and polarization in carbon emissions and carbon intensity. Further, we decompose the Kaya-Zenga index into different contributing factors both regionally and structurally and perform a scenario analysis to identify the corresponding regionally differentiated countermeasures regarding carbon emission reduction. The results show that the imbalance in carbon emissions is mainly caused by imbalances in population scale and income level, while the imbalance in carbon intensity predominantly results from imbalances in energy efficiency and energy mix. In addition, for heavy manufacturing provinces, the respective emission-reduction strategy should aim at lowering energy intensity through local technology improvement and inter-regional technology transfer. For light manufacturing and high technology provinces, carbon emission reduction is harder to be achieved; however, a mix of policies of improving energy efficiency, optimizing energy mix, and industrial upgrading should be implemented. The results of the scenario analysis indicate that reducing imbalance in carbon intensity under different scenarios can lead to a substantial reduction in carbon emissions (up to 10%). • We investigate the inter-provincial carbon imbalance within China. • We construct the Kaya-Zenga index and decompose the index into four contributors. • We use a panel data set of 30 provincial-level regions in China over 1995–2016. • Carbon imbalance is mainly caused by imbalances in population and energy efficiency. • Reducing intra-group imbalance in carbon intensity can abate carbon emissions. [ABSTRACT FROM AUTHOR]

This paper proposes a new methodology for measuring energy efficiency inequality based on the Shephard energy distance function and the "double" stochastic meta-frontier. To incorporate the regional inequality, we use three different grouping criteria, geography, city features, and strategic development goals. We also explore whether the different city grouping criteria can influence the energy efficiency. A panel data of 284 cities in China from 2003 to 2013 is used for empirical analysis. The results indicate that the regional heterogeneity has significant impact on the energy efficiency. We find that different grouping criteria affect energy efficiency, especially, the urban feature criteria. These results highlight the importance of choosing a proper grouping criteria in meta-frontier energy efficiency analysis. • The inequality of city-level energy efficiency needs evaluation. • We introduce the "double" stochastic meta-frontier method to perform analysis. • Three grouping criteria are proposed for visualizing the technology heterogeneity. • The regional heterogeneity different grouping criteria affect energy efficiency. • A proper grouping criterion is needed in meta-frontier analysis. [ABSTRACT FROM AUTHOR]